3 ms·
Andy from Carnegie Mellon here. This is impressive work. My PhD student and I have looked into similar methods for autotuning config knobs for MySQL + Postgres:
by apavlo 6y ago
Andy from Carnegie Mellon here. This is impressive work. My PhD student and I have looked into similar methods for autotuning config knobs for MySQL + Postgres: https://db.cs.cmu.edu/projects/ottertune/ https://db.cs.cmu.edu/projects/ottertune/
One of the many challenges with DB tuning that we have found is that people don't know whether their database, application, or DBMS version has changed enough to warrant another round of tuning. The best values that your tuning produces today may be different two weeks from now. Also, all the knobs that you are tuning don't require restarting the DBMS. Some of the knobs that make the most significant performance difference require you to restart the DBMS first before they take effect, which is not something people want to do often on their production database. None of the knobs that you target require restarting.
This problem is super interesting and our research has shown that it can really improve DB performance for some applications. We are in the process of spinning out OtterTune as a new startup: https://ottertune.com/ https://ottertune.com/
- ltbarcly3 6y agoI think the biggest improvement/effort thing you could look at for Postgresql is the cost estimates. It really does a poor job at estimating row counts (over/under estimating by multiple orders of magnitude quite often) when there are multiple joins, and the new extended statistics are for the most part useless for real scenarios that I have come across.